han dao-wen, liu wen-qing, zhang yu-jun, et al. Memorable glide window integral algorithm for retrieving cloud height[J]. High Power Laser and Particle Beams, 2008, 20.
Citation:
han dao-wen, liu wen-qing, zhang yu-jun, et al. Memorable glide window integral algorithm for retrieving cloud height[J]. High Power Laser and Particle Beams, 2008, 20.
han dao-wen, liu wen-qing, zhang yu-jun, et al. Memorable glide window integral algorithm for retrieving cloud height[J]. High Power Laser and Particle Beams, 2008, 20.
Citation:
han dao-wen, liu wen-qing, zhang yu-jun, et al. Memorable glide window integral algorithm for retrieving cloud height[J]. High Power Laser and Particle Beams, 2008, 20.
Key Laboratory of Environmental Optics and Technology,Anhui Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,P.O.Box 1125,Hefei 230031,China
The algorithm of retrieving cloud height was studied. The intensity and the pulse width of the cloud backscatter is different from the atmospheric aerosol and the random noise. The cloud height could be determined by analyzing lidar returns. A selected window gliding from the ground and the integral of signals in the window is calculated. The random noise could be eliminated and the cloud information could be distinguished from aerosol by window integral. Referred to previous cloud information, the current cloud height is retrieved according to the window integral. Compared with Vaisala ceilometer, the memorable glide window integral algorithm could be used to retrieve the information of cloud exactly and reliably.